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Lightweight Secure and Intelligent Approaches for Medical Devices

Trends and Future Frontiers

  • 1st Edition - April 1, 2027
  • Latest edition
  • Editors: R. Praveen, Karthik Ramamurthy
  • Language: English

Lightweight Secure and Intelligent Approaches for Medical Devices: Trends and Future Frontiers addresses the rapidly evolving intersection of artificial intelligence, Intern… Read more

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Description

Lightweight Secure and Intelligent Approaches for Medical Devices: Trends and Future Frontiers addresses the rapidly evolving intersection of artificial intelligence, Internet of Medical Things (IoMT), and edge computing within healthcare. This reference meets the critical demand for resource-efficient, secure, and trustworthy AI models tailored specifically for embedded medical devices operating under stringent constraints. By integrating advances in lightweight AI, medical device security, and intelligent data processing, the book fills a vital gap in current literature, offering researchers, engineers, and healthcare professionals a comprehensive resource to develop next-generation medical technologies. The book is organized into four parts, beginning with foundational concepts including the evolution of AI in healthcare devices, lightweight model design, and medical device security standards. It progresses to predictive intelligence and reliability, covering AI techniques for disease monitoring, device calibration, and personalized medicine. The security and privacy section explores network architectures, privacy-preserving AI, lightweight cryptography, and defenses against adversarial attacks. The final part presents emerging trends such as edge AI, digital twins, explainable AI, augmented and virtual reality applications, and quantum-safe security protocols. Each chapter combines theoretical insights with practical case studies and research perspectives to guide real-world deployment. Lightweight Secure and Intelligent Approaches for Medical Devices: Trends and Future Frontiers serves as an essential reference for researchers, medical device developers, cybersecurity professionals, and graduate students aiming to innovate secure and intelligent healthcare solutions in resource-constrained environments.

Key features

  • Presents unified frameworks integrating AI and security in medical devices
  • Explains lightweight AI model design optimized for low-power healthcare systems
  • Demonstrates application-centric case studies with real-world medical device examples
  • Highlights security mechanisms including lightweight cryptography and privacy preservation
  • Discusses future frontiers such as quantum-safe protocols and generative AI

Readership

Researchers and academics in Artificial Intelligence, Biomedical Engineering, Computer Science, and Healthcare Informatics who focus on lightweight AI, deep learning, and secure system architectures for medical devices

Table of contents

Part I: Foundations

1. Introduction to Secure and Intelligent Medical Devices

2. Evolution of AI in Healthcare Devices

3. Importance of Lightweight Models for Medical Devices and Medical Data Security

4. Balancing Prediction, Reliability and Security

5. Medical Device Standards and Security Regulations across Countries

6. Lightweight AI and Generative AI for Healthcare Systems

Part II: Prediction and Reliability

7. AI for Disease Prediction in Medical Devices

8. Innovative Lightweight AI Techniques for Chronic Disease Monitoring

9. AI-Powered Wearables and Implantable Edge Devices for Early Detection

10. Reliability and Performance Optimisation in Medical Devices

11. Predictive Maintenance of Critical Medical Equipment

12. AI-Driven Device Calibration and Fault Detection

13. Personalised and Precision Medicine with AI-Enabled Devices

Part III: Security and Privacy

14. Network Architectures for Medical Devices

15. Medical Data Security and Privacy-Preserving AI

16. Lightweight Secure Communication in IoMT

17. Adversarial Attacks and Robustness of AI Models in Healthcare

18. Quantum Technologies for Intelligent Healthcare

Part IV: Trends, Perspectives, and Future Frontiers

19. Edge AI and Digital Twins for Next-Generation Devices

20. Trustworthy and Explainable AI in Medical Devices

21. Transforming Healthcare: Augmented Reality (AR) and Virtual Reality (VR)

22. Emerging Trends in Generative AI for Healthcare Devices

23. Future Frontiers in Secure and Intelligent Medical Devices

24. Conclusion and Recommendations

Product details

  • Edition: 1
  • Latest edition
  • Published: April 1, 2027
  • Language: English

About the editors

RP

R. Praveen

Dr. R. Praveen is working as an Assistant Professor in the department of Computer Science and Engineering at National Institute of Technology Puducherry, Karaikal, India. He completed his Ph.D. in the Department of Computer Technology at Anna University, Chennai, India. He secured the first rank in the university during his master’s program. He is actively working in secure user authentication for the Internet of Medical Things (IoMT), cloud computing, decision-making models in wireless sensor networks and blockchain for Internet of Things (IoT) security. He is currently serving as an Academic Editor for PLOS One and editor in Scientific reports journal.

Affiliations and expertise
Assistant Professor, National Institute of Technology Puducherry, Karaikal, India

KR

Karthik Ramamurthy

Dr. Karthik Ramamurthy obtained his Doctoral degree from Vellore Institute of Technology, India and Master’s degree from Anna University, India. Currently, He serves as Associate Professor in the Research Centre for Cyber Physical Systems, Vellore Institute of Technology, Chennai. His research interest includes Artificial Intelligence, Deep Learning, Computer Vision, Digital Image Processing, and Medical Image Analysis. He has published around 80 papers in peer reviewed journals and conferences. He is an active reviewer for journals published by Elsevier, IEEE Springer and Nature.

Affiliations and expertise
Vellore Institute of Technology, Chennai, India